Epidemic phenomena are ubiquitous, ranging from infectious diseases, computer viruses, to information dissemination. Epidemics have traditionally been studied as a single spreading process, either in a fully mixed population or on a network. Many epidemics, however, are hybrid, employing more than one spreading mechanism. For example, the Internet worm Conficker spreads locally targeting neighbouring computers in local networks as well as globally by randomly probing any computer on the Internet. This thesis aims to investigate fundamental questions, such as whether a mix of spreading mechanisms gives hybrid epidemics any advantage, and what are the implications for promoting or mitigating such epidemics. We firstly propose a general and simple framework to model hybrid epidemics. Based on theoretical analysis and numerical simulations, we show that properties of hybrid epidemics are critically determined by a hybrid tradeoff, which defines the proportion of resource allocated to local and global spreading mechanisms. We then study two distinct examples of hybrid epidemics: the Internet worm Conficker and the Human Immunodeficiency Virus (HIV) infection within the human body. Using Internet measurement data, we reveal how Conficker combines ineffective spreading mechanisms to produce a serious outbreak on the Internet. We propose a mathematical model that can accurately recapitulate the entire HIV infection course as observed in clinical trials. Our study provides novel insights into the two parallel infection channels of HIV, i.e. cell-free spreading and cell-to-cell spreading, and their joint effect on HIV infection and treatment. In summary, this thesis has advanced our understanding of hybrid epidemics. It has provided mathematical frameworks for future analysis. It has demonstrated, with two successful case studies, that such research can have a significant impact on important issues such as cyberspace security and human health.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:668442 |
| Date | January 2015 |
| Creators | Zhang, C. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1468717/ |
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